Search Results for author:
Found 8 papers, 2 papers with code
Robustness Analysis on Foundational Segmentation Models
In this work, we perform a robustness analysis of Visual Foundation Models (VFMs) for segmentation tasks and focus on robustness against real-world distribution shift inspired perturbations.
A Large-Scale Robustness Analysis of Video Action Recognition Models
In this work, we perform a large-scale robustness analysis of these existing models for video action recognition.
Hybrid Active Learning via Deep Clustering for Video Action Detection
This hybrid strategy reduces the annotation cost from two different aspects leading to significant labeling cost reduction.
SVGraph: Learning Semantic Graphs from Instructional Videos
In this work, we focus on generating graphical representations of noisy, instructional videos for video understanding.
Robustness Analysis of Video-Language Models Against Visual and Language Perturbations
Joint visual and language modeling on large-scale datasets has recently shown good progress in multi-modal tasks when compared to single modal learning.
Self-Supervised Learning for Videos: A Survey
In this survey, we provide a review of existing approaches on self-supervised learning focusing on the video domain.
Novel View Video Prediction Using a Dual Representation
We address the problem of novel view video prediction; given a set of input video clips from a single/multiple views, our network is able to predict the video from a novel view.
PLM: Partial Label Masking for Imbalanced Multi-label Classification
By stochastically masking labels during loss computation, the method balances this ratio for each class, leading to improved recall on minority classes and improved precision on frequent classes.
